Iterative Methods for Waveform Control in Magnetic Measurement Systems

Magnetic losses in a ferromagnetic lamination can be separated into three contributions. Bertotti theoretically assessed this distribution at the end of twentieth century statistical theory (STLs), triggering significant progress understanding dissipation mechanisms. Recent studies have shown possibility reconstructing hysteresis cycle from high-frequency Barkhausen noise signal. Applying STL to cycles has never been done before. Still, it could help establish parallel with measurement magnetization versus frequency and energy loss. However, analysis its ultimate description requires sinusoidal flux density, while measurements are usually constant excitation slope. Multiple magnetic density control methods were described literature reviewed article. context, requiring sampling during cycle, is more constraining. Therefore, specific performance criteria considered, followed by numerical tests determine most adapted method description. Eventually, proportional iterative learning (P-ILC) gave highest satisfaction rate was chosen for experimental tests. Some these results provided article discussion together suggestions convergence speed improvement. It is, instance, recommended increase gain near saturation, where system response poor.